Monica Chiarini Tremblay

Communication Challenges in Requirements Elicitation and the Use of the Repertory Grid Technique

Requirements elicitation is a central and critical activity in the systems analysis and design process. This paper explores the nature of the challenges that confront analysts and their clients during requirements elicitation. A review of the literature highlights communication as a persistent locus of concern among systems analysts, users and procurers. The paper presents a classification of communication challenges that arise during the requirements elicitation process. Empirical evidence from a brief case study is used to illustrate the scope and impact of these communication challenges and to present a complementary approach to requirements elicitation. The paper introduces the Repertory Grid technique as a means to ameliorate some of the communication issues that persist, particularly in projects where information systems support specialized work. The paper is written in the form of a case tutorial, providing insight into the contribution of the Repertory Grid technique to requirements elicitation.

The Use of Focus Groups in Design Science Research

Focus groups to investigate new ideas are widely used in many research fields. The use of focus groups in design science research poses interesting opportunities and challenges. Traditional focus group methods must be adapted to meet two specific goals of design research. For the evaluation of an artifact design, exploratory focus groups (EFGs) study the artifact to propose improvements in the design. The results of the evaluation are used to refine the design and the cycle of build and evaluate using EFGs continues until the artifact is released for field test in the application environment. Then, the field test of the design artifact may employ confirmatory focus groups (CFGs) to establish the utility of the artifact in field use. Rigorous investigation of the artifact requires multiple CFGs to be run with opportunities for quantitative and qualitative data collection and analyses across the multiple CFGs. In this chapter, we discuss the adaptation of focus groups to design science research projects. We demonstrate the use of both EFGs and CFGs in a design research doctoral thesis in the health-care field.

Doing more with more information: Changing healthcare planning with OLAP tools

On-line analytical processing (OLAP) is an example of a new breed of tools for decision support that give decision makers the flexibility to customize the selection, aggregation, and presentation of data. To understand the impact of this type of tool, we study an implementation of an OLAP interface on the CATCH data warehouse used by knowledge workers at a regional health planning agency in the State of Florida. The results of a qualitative field study show that after the OLAP implementation, these workers made use of the additional capabilities of OLAP (e.g., aggregation levels and intuitive data manipulation), thereby leveraging their individual abilities to enhance and expand on the tasks they performed for their community. Consequently, they were able to perform in more of a consultative role to their clients, and improved their reputation in the community they serve. This research adds a new dimension to prior research in data warehousing by focusing on the decision support capabilities of OLAP.

Identifying fall-related injuries: Text mining the electronic medical record

Unintentional injury due to falls is a serious and expensive health problem among the elderly. This is especially true in the Veterans Health Administration (VHA) ambulatory care setting, where nearly 40% of the male patients are 65 or older and at risk for falls. Health service researchers and clinicians can utilize VHA administrative data to identify and explore the frequency and nature of fall-related injuries (FRI) to aid in the implementation of clinical and prevention programs. Here we define administrative data as structured (coded) values that are generated as a result clinical services provided to veterans and stored in databases. However, the limitations of administrative data do not always allow for conclusive decision making, especially in areas where coding may be incomplete. This study utilizes data and text mining techniques to investigate if unstructured text-based information included in the electronic medical record can validate and enhance those records in the administrative data that should have been coded as fall-related injuries. The challenges highlighted by this study include data extraction and preparation from administrative sources and the full electronic medical records, de-indentifying the data (to assure HIPAA compliance), conducting chart reviews to construct a “gold standard” dataset, and performing both supervised and unsupervised text mining techniques in comparison with traditional medical chart review.

Focus groups and critical social IS research: How the choice of method can promote emancipation of respondents and researchers.

Critical social research in information systems has been gaining prominence for some time and is increasingly viewed as a valid research approach. One problem with the critical tradition is a lack of empirical research. A contributing factor to this gap in the literature is the lack of agreement on what constitutes appropriate methodologies for critical research. The present paper contributes to this debate by exploring the role that focus group research can play in the critical approach. This paper outlines the main characteristics of critical research with an emphasis on its emancipatory faculties. It then reviews the focus group method from the perspective of critical approach and provides a critical account of two research projects that used focus groups as a method of data collection. The paper presents the argument that focus groups, if designed and executed in light of a critical approach, can contribute to the emancipation of researchers and respondents. This argument is built upon the critical theories of the two most influential theorists in critical social information systems research, namely Jürgen Habermas and Michel Foucault. Critically oriented focus groups have the potential to improve communication and move real discourses closer to Habermass ideal speech situation. At the same time, they can contribute to challenging the prevailing orthodoxy and thereby overcome established regimes of truth in the Foucauldian tradition. The paper ends by developing a set of guiding questions that provide a means for researchers to ensure that the emancipatory potential of focus group research can be achieved.

Design of an information volatility measure for health care decision making

Health care decision makers and researchers often use reporting tools (e.g. Online Analytical Processing (OLAP)) that present data aggregated from multiple medical registries and electronic medical records to gain insights into health care practices and to understand and improve patient outcomes and quality of care. An important limitation is that the data are usually displayed as point estimates without full description of the instability of the underlying data, thus decision makers are often unaware of the presence of outliers or data errors. To manage this problem, we propose an Information Volatility Measure (IVM) to complement business intelligence (BI) tools when considering aggregated data (intra-cell) or when observing trends in data (inter-cell). The IVM definitions and calculations are drawn from volatility measures found in the field of finance, since the underlying data in both arenas display similar behaviors. The presentation of the IVM is supplemented with three types of benchmarking to support improved user understanding of the measure: numerical benchmarking, graphical benchmarking, and categorical benchmarking. The IVM is designed and evaluated using exploratory and confirmatory focus groups.

Advancing the Impact of Design Science: Moving from Theory to Practice

Although sustainability is a key concern in today’s world, more efforts towards achieving sustainability are needed. User inclusion in the information system design process could enhance the outcome of a system’s action towards sustainability. It is, however, important to understand the design procedure of a system to achieve such goals. A framework denominating as the inclusive innovation framework presented in this paper incorporated analyses from open innovation, universal design, and sustainability to motivate the initiation of internal and external driving factors towards sustainability goals. The derived framework could promote the information system’s enabled sustainable goals by combining the use of universal design principles and the concept of open innovation. A requirement engineering model was also proposed that was interoperable within the three subjects of interest discussed in the paper and was necessary for understanding the application of an inclusive innovation framework. Two use cases were then presented as an illustration for arguing the validation of the proposed inclusive innovation framework. The findings from the use cases indicated that the use of universal design principles along with an open innovation concept could increase information systems’ enabled sustainability goals. This could be done by enhancing a system’s successfulness along with the increased user satisfaction.

IT Governance Characteristics, Electronic Medical Records Sophistication, and Financial Performance in U.S. Hospitals: An Empirical Investigation

As a result of a recent federal government mandate, an increasing number of hospitals have decided to adopt electronic medical record (EMR) systems. This initiative is expected to lead toward more efficient and higher quality health care; however, little is known about governance characteristics and organizational performance for EMR adopters. Our goal is to inform theory and practice by examining hospitals with a sophisticated EMR and comparing those hospitals to similar hospitals (with a less sophisticated EMR) to understand the association between information technology (IT) governance characteristics and the implications on financial performance. Leveraging elements of the upper echelon theory, we posit that hospitals in which the chief information officer (CIO) reports to the chief executive officer, CIO turnover is low, and an IT steering committee is present are more likely to have a sophisticated EMR. We argue that EMR sophistication leads to improved financial performance. Our results underscore the importance of continuity in the CIO position on successful EMR implementations. Results also show that hospital size and financial performance are strongly associated with EMR sophistication. In addition, we find that a sophisticated EMR appears to be a fundamental element in improving hospitals’ revenue cycle management. Moreover, we find that hospitals with a sophisticated EMR appear to be more profitable. Finally, we observe that total payroll expense adjusted by total discharges drops among the sophisticated hospitals, potentially due to an increase in employee productivity. These insights can serve as a basis for tempering expectations relative to the financial impact of EMR adoption.

Using Data Mining Techniques to Discover Bias Patterns in Missing Data

In today’s data-rich environment, decision makers draw conclusions from data repositories that may contain data quality problems. In this context, missing data is an important and known problem, since it can seriously affect the accuracy of conclusions drawn. Researchers have described several approaches for dealing with missing data, primarily attempting to infer values or estimate the impact of missing data on conclusions. However, few have considered approaches to characterize patterns of bias in missing data, that is, to determine the specific attributes that predict the missingness of data values. Knowledge of the specific systematic bias patterns in the incidence of missing data can help analysts more accurately assess the quality of conclusions drawn from data sets with missing data. This research proposes a methodology to combine a number of Knowledge Discovery and Data Mining techniques, including association rule mining, to discover patterns in related attribute values that help characterize these bias patterns. We demonstrate the efficacy of our proposed approach by applying it on a demo census dataset seeded with biased missing data. The experimental results show that our approach was able to find seeded biases and filter out most seeded noise.

A review of the literature and proposed classification on e-prescribing: Functions, assimilation stages, benefits, concerns, and risks

BACKGROUND Evidence from the literature indicates that besides its benefits, e-prescribing also generates new types of unintended medication errors that have the potential to harm patient safety. Analyzing both the benefits and risks of e-prescribing can give health care organizations a better understanding of the improvements gained and errors generated by this technology. OBJECTIVES To review the primary functions of e-prescribing and its assimilation stages in the health care context. This review also aims to classify the potential benefits, risks and concerns associated with e-prescribing along with factors contributing to e-prescribing errors. METHODS A literature review was conducted primarily in Web of Sciences electronic databases. The online databases were searched for both peer-reviewed quantitative and qualitative research papers written in English and published between January 2008 and December 2014 (i.e., the last seven years). Several additional studies were also accessed through Google Scholar and the citations of the selected articles. A total of 73 publications met the studys inclusion criteria. RESULTS The key benefits of e-prescribing were identified as improving the quality of health care services, increasing the efficiency and effectiveness of prescribing and dispensing medications, reducing medication errors, and health care cost savings. Failure to properly implement e-prescribing systems can also result in new types of errors that reduce workflow efficiency, increase medication cost, and threaten patient safety. In this study, factors contributing to potential errors were categorized into four primary groups (human, technical, interaction and organizational errors). CONCLUSIONS This review identified the primary benefits and risks of e-prescribing services. The study contributes to the body of knowledge related to the design, adoption and use of e-prescribing by providing a clear reflection on its potential gains and risks. Based on the findings of this review, conducting research in several areas is quite promising as future work. This review also has practical implications for health care providers, e-prescribing software vendors and policy makers.